Global Disease Outbreaks Associated with the 2015-2016 El Niño Event

Emergence of infectious diseases and role of advanced nanomaterials in point-of-care diagnostics: a review

Infectious outbreaks are the foremost global public health concern, challenging the current healthcare system, which claims millions of lives annually. The most crucial way to control an infectious outbreak is by early detection through point-of-care (POC) diagnostics. POC diagnostics are highly advantageous owing to the prompt diagnosis, which is economical, simple and highly efficient with remote access capabilities. In particular, utilization of nanomaterials to architect POC devices has enabled highly integrated and portable (compact) devices with enhanced efficiency. As such, this review will detail the factors influencing the emergence of infectious diseases and methods for fast and accurate detection, thus elucidating the underlying factors of these infections. Furthermore, it comprehensively highlights the importance of different nanomaterials in POCs to detect nucleic acid, whole pathogens, proteins and antibody detection systems. Finally, we summarize findings reported on nanomaterials based on advanced POCs such as lab-on-chip, lab-on-disc-devices, point-of-action and hospital-on-chip. To this end, we discuss the challenges, potential solutions, prospects of integrating internet-of-things, artificial intelligence, 5G communications and data clouding to achieve intelligent POCs.

Causal association between environmental variables and the excess cases of cutaneous leishmaniasis in Colombia: are we looking to the wrong side?

Our main aim was to estimate and compare the effects of six environmental variables (air temperature, soil temperature, rainfall, runoff, soil moisture, and the enhanced vegetation index) on excess cases of cutaneous leishmaniasis in Colombia. We used epidemiological data from the Colombian Public Health Surveillance System (January 2007 to December 2019). Environmental data were obtained from remote sensing sources including the National Oceanic and Atmospheric Administration, the Global Land Data Assimilation System (GLDAS), and the Moderate Resolution Imaging Spectroradiometer. Data on population were obtained from the TerriData dataset. We implemented a causal inference approach using a machine learning algorithm to estimate the causal association of the environmental variables on the monthly occurrence of excess cases of cutaneous leishmaniasis. The results showed that the largest causal association corresponded to soil moisture with a lag of 3 months, with an average increase of 8.0% (95% confidence interval [CI] 7.7-8.3%) in the occurrence of excess cases. The temperature-related variables (air temperature and soil temperature) had a positive causal effect on the excess cases of cutaneous leishmaniasis. It is noteworthy that rainfall did not have a statistically significant causal effect. This information could potentially help to monitor and control cutaneous leishmaniasis in Colombia, providing estimates of causal effects using remote sensor variables.

Effects of the El Niño-Southern Oscillation and seasonal weather conditions on Aedes aegypti infestation in the State of São Paulo (Brazil): A Bayesian spatio-temporal study

BACKGROUND

Seasonal fluctuations in weather are recognized as factors that affect both Aedes (Ae.) aegypti mosquitoes and the diseases they carry, such as dengue fever. The El Niño-Southern Oscillation (ENSO) is widely regarded as one of the most impactful atmospheric phenomena on Earth, characterized by the interplay of shifting ocean temperatures, trade wind intensity, and atmospheric pressure, resulting in extensive alterations in climate conditions. In this study, we investigate the influence of ENSO and local weather conditions on the spatio-temporal variability of Ae. aegypti infestation index.

METHODS

We collected seasonal entomological survey data of immature forms of Ae. aegypti mosquitoes (Breteau index), as well as data on temperature, rainfall and the Oceanic Niño Index (ONI) for the period 2008-2018 over the 645 municipalities of the subtropical State of São Paulo (Brazil). We grounded our analytical approach on a Bayesian framework and we used a hierarchical spatio-temporal model to study the relationship between ENSO tracked by ONI, seasonal weather fluctuations and the larval index, while adjusting for population density and wealth inequalities.

RESULTS

Our results showed a relevant positive effect for El Niño on the Ae. aegypti larval index. In particular, we found that the number of positive containers would be expected to increase by 1.30-unit (95% Credible Intervals (CI): 1.23 to 1.37) with El Niño events (i.e., ≥ 1°C, moderate to strong) respect to neutral (and weak) events. We also found that seasonal rainfall exceeding 153.12 mm appears to have a notable impact on vector index, leading potentially to the accumulation of ample water in outdoor discarded receptacles, supporting the aquatic phase of mosquito development. Additionally, seasonal temperature above 23.30°C was found positively associated to the larval index. Although the State of São Paulo as a whole has characteristics favourable to proliferation of the vector, there were specific areas with a greater tendency for mosquito infestation, since the most vulnerable areas are predominantly situated in the central and northern regions of the state, with hot spots of abundance in the south, especially during El Niño events. Our findings also indicate that social disparities present in the municipalities contributes to Ae. aegypti proliferation.

CONCLUSIONS

Considering the anticipated rise in both the frequency and intensity of El Niño events in the forthcoming decades as a consequence of climate change, the urgency to enhance our ability to track and diminish arbovirus outbreaks is crucial.

A thirty-year time series analyses identifies coherence between oscillations in Anthrax outbreaks and El Niño in Karnataka, India

Anthrax is an economically important zoonotic disease affecting both livestock and humans. The disease is caused by a spore forming bacterium, Bacillus anthracis, and is considered endemic to the state of Karnataka, India. It is critical to quantify the role of climatic factors in determining the temporal pattern of anthrax outbreaks, so that reliable forecasting models can be developed. These models will aid in establishing public health surveillance and guide strategic vaccination programs, which will reduce the economic loss to farmers, and prevent the spill-over of anthrax from livestock to humans. In this study, correlation and coherence between time series of anthrax outbreaks in livestock (1987-2016) and meteorological variables and Sea Surface Temperature anomalies (SST) were identified using a combination of cross-correlation analyses, spectral analyses (wavelets and empirical mode decomposition) and further quantified using a Bayesian time series regression model accounting for temporal autocorrelation. Monthly numbers of anthrax outbreaks were positively associated with a lagged effect of rainfall and wet day frequency. Long-term periodicity in anthrax outbreaks (approximately 6-8 years) was coherent with the periodicity in SST anomalies and outbreak numbers increased with decrease in SST anomalies. These findings will be useful in planning long-term anthrax prevention and control strategies in Karnataka state of India.

Global risk of Dengue outbreaks and the impact of El Niño events

BACKGROUND

Dengue fever is an arboviral disease caused by the dengue virus (DENV). Its geographical distribution and health burden have been steadily increasing through tropical and subtropical climates in recent decades.

METHODS

We developed a temperature- and precipitation-dependent mechanistic model for the global risk of dengue fever outbreaks using the basic reproduction number (R0) as the metric of disease transmission risk. We used our model to evaluate the global risk of dengue outbreaks from 1950-2020 and to investigate the impact of annual seasons and El Niño events.

RESULTS

We showed that the global annual risk of dengue outbreaks has steadily increased during the last four decades. Highest R0 values were observed in South America, Southeast Asia, and the Equatorial region of Africa year-round with large seasonal variations occurring in other regions. El Niño was shown to be positively correlated with the global risk of dengue outbreaks with a correlation of 0.52. However, the impact of El Niño on dengue R0 was shown to vary across geographical regions and between El Niño events.

CONCLUSIONS

Strong El Niño events may increase the risk of dengue outbreaks across the globe. The onset of these events may trigger a surge of control efforts to minimize risk of dengue outbreaks.

The global incidence and trends of three common flavivirus infections (Dengue, yellow fever, and Zika) from 2011 to 2021

Background

Flavivirus pose a continued threat to global health, yet their worldwide burden and trends remain poorly quantified. We aimed to evaluate the global, regional, and national incidence of three common flavivirus infections (Dengue, yellow fever, and Zika) from 2011 to 2021.

Methods

Data on the number and rate of incidence for the three common flavivirus infection in 204 countries and territories were retrieved from the Global Burden of Diseases, Injuries, and Risk Factors Study (GBD) 2021. The estimated annual percent change (EAPC) was calculated to quantify the temporal trend during 2011-2016, 2016-2019, and 2019-2021, respectively.

Results

In 2021, an estimated 59,220,428 individuals were infected globally, comprising 58,964,185 cases of dengue, 86,509 cases of yellow fever, and 169,734 cases of Zika virus infection. The age-standardized incidence rate (ASIR) of the three common flavivirus infections increased by an annual average of 5.08% (95% CI 4.12 to 6.05) globally from 2011 to 2016, whereas decreased by an annual average of -8.37% (95% CI -12.46 to -4.08) per year between 2016 to 2019. The ASIR remained stable during 2019-2021, with an average change of 0.69% (95% CI -0.96 to 2.37) per year globally for the three common flavivirus infections. Regionally, the burden of the three common flavivirus infections was primarily concentrated in those regions with middle income, such as South Asia, Southeast Asia, and Tropical Latin America. Additionally, at the country level, there was an inverted "U" relationship between the SDI level and the ASI. Notably, an increase in the average age of infected cases has been observed worldwide, particularly in higher-income regions.

Conclusion

Flavivirus infections are an expanding public health concern worldwide, with considerable regional and demographic variation in the incidence. Policymakers and healthcare providers must stay vigilant regarding the impact of COVID-19 and other environmental factors on the risk of flavivirus infection and be prepared for potential future outbreaks.

Hantavirus Expansion Trends in Natural Host Populations in Brazil

Hantaviruses are zoonotic agents responsible for causing Hantavirus Cardiopulmonary Syndrome (HCPS) in the Americas, with Brazil ranking first in number of confirmed HCPS cases in South America. In this study, we simulate the monthly spread of highly lethal hantavirus in natural hosts by conjugating a Kermack-McCormick SIR model with a cellular automata model (CA), therefore simultaneously evaluating both in-cell and between-cell infection dynamics in host populations, using recently compiled data on main host species abundances and confirmed deaths by hantavirus infection. For both host species, our models predict an increase in the area of infection, with 22 municipalities where no cases have been confirmed to date expected to have at least one case in the next decade, and a reduction in infection in 11 municipalities. Our findings support existing research and reveal new areas where hantavirus is likely to spread within recognized epicenters. Highlighting spatial-temporal trends and potential expansion, we emphasize the increased risk due to pervasive habitat fragmentation and agricultural expansion. Consistent prevention efforts and One Health actions are crucial, especially in newly identified high-risk municipalities.

Maternal preconceptional and prenatal exposure to El Niño Southern Oscillation levels and child mortality: a multi-country study

El Niño Southern Oscillation (ENSO) has been shown to relate to the epidemiology of childhood infectious diseases, but evidence for whether they increase child deaths is limited. Here, we investigate the impact of mothers' ENSO exposure during and prior to delivery on child mortality by constructing a retrospective cohort study in 38 low- and middle-income countries. We find that high levels of ENSO indices cumulated over 0-12 lagged months before delivery are associated with significant increases in risks of under-five mortality; with the hazard ratio ranging from 1.33 (95% confidence interval [CI], 1.26, 1.40) to 1.89 (95% CI, 1.78, 2.00). Child mortality risks are particularly related to maternal exposure to El Niño-like conditions in the 0th-1st and 6th-12th lagged months. The El Niño effects are larger in rural populations and those with unsafe sources of drinking water and less education. Thus, preventive interventions are particularly warranted for the socio-economically disadvantaged.

Broadscale spatial synchrony in a West Nile virus mosquito vector across multiple timescales

Insects often exhibit irruptive population dynamics determined by environmental conditions. We examine if populations of the Culex tarsalis mosquito, a West Nile virus (WNV) vector, fluctuate synchronously over broad spatial extents and multiple timescales and whether climate drives synchrony in Cx. tarsalis, especially at annual timescales, due to the synchronous influence of temperature, precipitation, and/or humidity. We leveraged mosquito collections across 9 National Ecological Observatory Network (NEON) sites distributed in the interior West and Great Plains region USA over a 45-month period, and associated gridMET climate data. We utilized wavelet phasor mean fields and wavelet linear models to quantify spatial synchrony for mosquitoes and climate and to calculate the importance of climate in explaining Cx. tarsalis synchrony. We also tested whether the strength of spatial synchrony may vary directionally across years. We found significant annual synchrony in Cx. tarsalis, and short-term synchrony during a single period in 2018. Mean minimum temperature was a significant predictor of annual Cx. tarsalis spatial synchrony, and we found a marginally significant decrease in annual Cx. tarsalis synchrony. Significant Cx. tarsalis synchrony during 2018 coincided with an anomalous increase in precipitation. This work provides a valuable step toward understanding broadscale synchrony in a WNV vector.

Spatiotemporal Characterization of Dengue Incidence and Its Correlation to Climate Parameters in Indonesia

Dengue has become a public health concern in Indonesia since it was first found in 1968. This study aims to determine dengue hotspot areas and analyze the spatiotemporal distribution of dengue and its association with dominant climate parameters nationally. Monthly data for dengue and climate observations (i.e., rainfall, relative humidity, average, maximum, and minimum temperature) at the regency/city level were utilized. Dengue hotspot areas were determined through K-means clustering, while Singular Value Decomposition (SVD) determined dominant climate parameters and their spatiotemporal distribution. Results revealed four clusters: Cluster 1 comprised cities with medium to high Incidence Rates (IR) and high Case Densities (CD) in a narrow area. Cluster 2 has a high IR and low CD, and clusters 3 and 4 featured medium and low IR and CD, respectively. SVD analysis indicated that relative humidity and rainfall were the most influential parameters on IR across all clusters. Temporal fluctuations in the first mode of IR and climate parameters were clearly delineated. The spatial distribution of heterogeneous correlation between the first mode of rainfall and relative humidity to IR exhibited higher values, which were predominantly observed in Java, Bali, Nusa Tenggara, the eastern part of Sumatra, the southern part of Kalimantan, and several locations in Sulawesi.

Investigation of the Correlation between Enterovirus Infection and the Climate Factor Complex Including the Ping-Year Factor and El Niño-Southern Oscillation in Taiwan

Enterovirus infection and enterovirus infection with severe complications (EVSC) are critical issues in several aspects. However, there is no suitable predictive tool for these infections. A climate factor complex (CFC) containing several climate factors could provide more effective predictions. The ping-year factor (PYF) and El Niño-Southern Oscillation (ENSO) are possible CFCs. This study aimed to determine the relationship between these two CFCs and the incidence of enterovirus infection. Children aged 15 years and younger with enterovirus infection and/or EVSC were enrolled between 2007 and 2022. Each year was categorized into a ping-year or non-ping-year according to the PYF. Poisson regression was used to evaluate the associations between the PYF, ENSO, and the incidence of enterovirus infection. Compared to the ping-year group, the incidence rate of enterovirus infection, the incidence rate of EVSC, and the ratio of EVSC in the non-ping-year group were 1.24, 3.38, and 2.73 times higher, respectively (p < 0.001). For every one-unit increase in La Niña, the incidence rate of enterovirus infection decreased to 0.96 times (p < 0.001). Our study indicated that CFCs could be potential predictors for enterovirus infection, and the PYF was more suitable than ENSO. Further research is needed to improve the predictive model.

Spatial and temporal trends of dengue infections in Curaçao: A 21-year analysis

Dengue viruses are a significant global health concern, causing millions of infections annually and putting approximately half of the world's population at risk, as reported by the World Health Organization (WHO). Understanding the spatial and temporal patterns of dengue virus spread is crucial for effective prevention of future outbreaks. By investigating these patterns, targeted dengue surveillance and control measures can be improved, aiding in the management of outbreaks in dengue-affected regions. Curaçao, where dengue is endemic, has experienced frequent outbreaks over the past 25 years. To examine the spatial and temporal trends of dengue outbreaks in Curaçao, this study employs an interdisciplinary and multi-method approach. Data on >6500 cases of dengue infections in Curaçao between the years 1995 and 2016 were used. Temporal and spatial statistics were applied. The Moran's I index identified the presence of spatial autocorrelation for incident locations, allowing us to reject the null hypothesis of spatial randomness. The majority of cases were recorded in highly populated areas and a relationship was observed between population density and dengue cases. Temporal analysis demonstrated that cases mostly occurred from October to January, during the rainy season. Lower average temperatures, higher precipitation and a lower sea surface temperature appear to be related to an increase in dengue cases. This effect has a direct link to La Niña episodes, which is the cooling phase of El Niño Southern Oscillation. The spatial and temporal analyses conducted in this study are fundamental to understanding the timing and locations of outbreaks, and ultimately improving dengue outbreak management.

A New Paradigm for Pandemic Preparedness

Purpose of Review

Preparing for pandemics requires a degree of interdisciplinary work that is challenging under the current paradigm. This review summarizes the challenges faced by the field of pandemic science and proposes how to address them.

Recent Findings

The structure of current siloed systems of research organizations hinders effective interdisciplinary pandemic research. Moreover, effective pandemic preparedness requires stakeholders in public policy and health to interact and integrate new findings rapidly, relying on a robust, responsive, and productive research domain. Neither of these requirements are well supported under the current system.

Summary

We propose a new paradigm for pandemic preparedness wherein interdisciplinary research and close collaboration with public policy and health practitioners can improve our ability to prevent, detect, and treat pandemics through tighter integration among domains, rapid and accurate integration, and translation of science to public policy, outreach and education, and improved venues and incentives for sustainable and robust interdisciplinary work.

Mitigating the effects of climate change on human health with vaccines and vaccinations

Climate change represents an unprecedented threat to humanity and will be the ultimate challenge of the 21st century. As a public health consequence, the World Health Organization estimates an additional 250,000 deaths annually by 2030, with resource-poor countries being predominantly affected. Although climate change's direct and indirect consequences on human health are manifold and far from fully explored, a growing body of evidence demonstrates its potential to exacerbate the frequency and spread of transmissible infectious diseases. Effective, high-impact mitigation measures are critical in combating this global crisis. While vaccines and vaccination are among the most cost-effective public health interventions, they have yet to be established as a major strategy in climate change-related health effect mitigation. In this narrative review, we synthesize the available evidence on the effect of climate change on vaccine-preventable diseases. This review examines the direct effect of climate change on water-related diseases such as cholera and other enteropathogens, helminthic infections and leptospirosis. It also explores the effects of rising temperatures on vector-borne diseases like dengue, chikungunya, and malaria, as well as the impact of temperature and humidity on airborne diseases like influenza and respiratory syncytial virus infection. Recent advances in global vaccine development facilitate the use of vaccines and vaccination as a mitigation strategy in the agenda against climate change consequences. A focused evaluation of vaccine research and development, funding, and distribution related to climate change is required.

El Niño Southern Oscillation (ENSO) effects on local weather, arboviral diseases, and dynamics of managed and unmanaged populations of Aedes aegypti (Diptera: Culicidae) in Puerto Rico

We investigated the effects of interannual El Niño Southern Oscillation (ENSO) events on local weather, Aedes aegypti populations, and combined cases of dengue (DENV), chikungunya (CHIKV), and Zika (ZIKV) viruses in 2 communities with mass mosquito trapping and 2 communities without mosquito control in southern Puerto Rico (2013-2019). Gravid adult Ae. aegypti populations were monitored weekly using Autocidal Gravid Ovitraps (AGO traps). Managing Ae. aegypti populations was done using 3 AGO traps per home in most homes. There were drought conditions in 2014-2015 concurrent with the emergence of a strong El Niño (2014-2016), wetter conditions during La Niña (2016-2018), a major hurricane (2017), and a weaker El Niño (2018-2019). The main factor explaining differences in Ae. aegypti abundance across sites was mass trapping. Populations of Ae. aegypti reached maximum seasonal values during the wetter and warmer months of the year when arbovirus epidemics occurred. El Niño was significantly associated with severe droughts that did not impact the populations of Ae. aegypti. Arbovirus cases at the municipality level were positively correlated with lagged values (5-12 mo.) of the Oceanic El Niño Index (ONI), droughts, and abundance of Ae. aegypti. The onset of strong El Niño conditions in Puerto Rico may be useful as an early warning signal for arboviral epidemics in areas where the abundance of Ae. aegypti exceeds the mosquito density threshold value.

The Impact of Human Activities on Zoonotic Infection Transmissions

As humans expand their territories across more and more regions of the planet, activities such as deforestation, urbanization, tourism, wildlife exploitation, and climate change can have drastic consequences for animal movements and animal-human interactions. These events, especially climate change, can also affect the arthropod vectors that are associated with the animals in these scenarios. As the COVID-19 pandemic and other various significant outbreaks throughout the centuries have demonstrated, when animal patterns and human interactions change, so does the exposure of humans to zoonotic pathogens potentially carried by wildlife. With approximately 60% of emerging human pathogens and around 75% of all emerging infectious diseases being categorized as zoonotic, it is of great importance to examine the impact of human activities on the prevalence and transmission of these infectious agents. A better understanding of the impact of human-related factors on zoonotic disease transmission and prevalence can help drive the preventative measures and containment policies necessary to improve public health.

Ecological Niche Modelling Approaches: Challenges and Applications in Vector-Borne Diseases

Vector-borne diseases (VBDs) pose a major threat to human and animal health, with more than 80% of the global population being at risk of acquiring at least one major VBD. Being profoundly affected by the ongoing climate change and anthropogenic disturbances, modelling approaches become an essential tool to assess and compare multiple scenarios (past, present and future), and further the geographic risk of transmission of VBDs. Ecological niche modelling (ENM) is rapidly becoming the gold-standard method for this task. The purpose of this overview is to provide an insight of the use of ENM to assess the geographic risk of transmission of VBDs. We have summarised some fundamental concepts and common approaches to ENM of VBDS, and then focused with a critical view on a number of crucial issues which are often disregarded when modelling the niches of VBDs. Furthermore, we have briefly presented what we consider the most relevant uses of ENM when dealing with VBDs. Niche modelling of VBDs is far from being simple, and there is still a long way to improve. Therefore, this overview is expected to be a useful benchmark for niche modelling of VBDs in future research.

Cholera Dynamics and the Emergence of Pandemic Vibrio cholerae

Cholera is a severe diarrheal disease caused by the aquatic bacterium Vibrio cholerae. Interestingly, to date, only one major clade has emerged to cause pandemic disease in humans: the clade that encompasses the strains from the O1 and O139 serogroups. In this chapter, we provide a comprehensive perspective on the virulence factors and mobile genetic elements (MGEs) associated with the emergence of pandemic V. cholerae strains and highlight novel findings such as specific genomic background or interactions between MGEs that explain their confined distribution. Finally, we discuss pandemic cholera dynamics contextualizing them within the evolution of the bacterium.

Multisectoral Perspectives on Global Warming and Vector-borne Diseases: a Focus on Southern Europe

Purpose of Review

The climate change (CC) or global warming (GW) modifies environment that favors vectors' abundance, growth, and reproduction, and consequently, the rate of development of pathogens within the vectors. This review highlights the threats of GW-induced vector-borne diseases (VBDs) in Southern Europe (SE) and the need for mitigation efforts to prevent potential global health catastrophe.

Recent Findings

Reports showed astronomical surges in the incidences of CC-induced VBDs in the SE. The recently (2022) reported first cases of African swine fever in Northern Italy and West Nile fever in SE are linked to the CC-modified environmental conditions that support vectors and pathogens' growth and development, and disease transmission.

Summary

VBDs endemic to the tropics are increasingly becoming a major health challenge in the SE, a temperate region, due to the favorable environmental conditions caused by CC/GW that support vectors and pathogens' biology in the previously non-endemic temperate regions.

Nipah Virus Disease: Epidemiological, Clinical, Diagnostic and Legislative Aspects of This Unpredictable Emerging Zoonosis

Nipah virus (NiV) infection is a viral disease caused by a Henipavirus, belonging to the Paramyxoviridae family, responsible for a zoonosis. The course of the disease can be very serious and lead to death. NiV natural hosts are fruit bats (also known as megabats) belonging to the Pteropodidae family, especially those of the Pteropus genus. Natural infection in domestic animals has been described in farming pigs, horses, domestic and feral dogs and cats. Natural NiV transmission is possible intra-species (pig-to-pig, human-to-human) and inter-species (flying bat-to-human, pig-to-human, horse-to-human). The infection can be spread by humans or animals in different ways. It is peculiar how the viral transmission modes among different hosts also change depending on the geographical area for different reasons, including different breeding methods, eating habits and the recently identified genetic traits/molecular features of main virus proteins related to virulence. Outbreaks have been described in Malaysia, Singapore, Bangladesh, India and the Philippines with, in some cases, severe respiratory and neurological disease and high mortality in both humans and pigs. Diagnosis can be made using different methods including serological, molecular, virological and immunohistochemical methods. The cornerstones for control of the disease are biosecurity (via the correct management of reservoir and intermediate/amplifying hosts) and potential vaccines which are still under development. However, the evaluation of the potential influence of climate and anthropogenic changes on the NiV reservoir bats and their habitat as well as on disease spread and inter-specific infections is of great importance. Bats, as natural reservoirs of the virus, are responsible for the viral spread and, therefore, for the outbreaks of the disease in humans and animals. Due to the worldwide distribution of bats, potential new reports and spillovers are not to be dismissed in the future.

Impacts of climate change and environmental degradation on children in Malaysia

The impacts of climate change and degradation are increasingly felt in Malaysia. While everyone is vulnerable to these impacts, the health and wellbeing of children are disproportionately affected. We carried out a study composed of two major components. The first component is an environmental epidemiology study comprised of three sub-studies: (i) a global climate model (GCM) simulating specific health-sector climate indices; (ii) a time-series study to estimate the risk of childhood respiratory disease attributable to ambient air pollution; and (iii) a case-crossover study to identify the association between haze and under-five mortality in Malaysia. The GCM found that Malaysia has been experiencing increasing rainfall intensity over the years, leading to increased incidences of other weather-related events. The time-series study revealed that air quality has worsened, while air pollution and haze have been linked to an increased risk of hospitalization for respiratory diseases among children. Although no clear association between haze and under-five mortality was found in the case-crossover study, the lag patterns suggested that health effects could be more acute if haze occurred over a longer duration and at a higher intensity. The second component consists of three community surveys on marginalized children conducted (i) among the island community of Pulau Gaya, Sabah; (ii) among the indigenous Temiar tribe in Pos Kuala Mu, Perak; and (iii) among an urban poor community (B40) in PPR Sg. Bonus, Kuala Lumpur. The community surveys are cross-sectional studies employing a socio-ecological approach using a standardized questionnaire. The community surveys revealed how children adapt to climate change and environmental degradation. An integrated model was established that consolidates our overall research processes and demonstrates the crucial interconnections between environmental challenges exacerbated by climate change. It is recommended that Malaysian schools adopt a climate-smart approach to education to instill awareness of the impending climate change and its cascading impact on children's health from early school age.

Predicting COVID-19 Cases in South Korea Using Stringency and Niño Sea Surface Temperature Indices

Most coronavirus disease 2019 (COVID-19) models use a combination of agent-based and equation-based models with only a few incorporating environmental factors in their prediction models. Many studies have shown that human and environmental factors play huge roles in disease transmission and spread, but few have combined the use of both factors, especially for SARS-CoV-2. In this study, both man-made policies (Stringency Index) and environment variables (Niño SST Index) were combined to predict the number of COVID-19 cases in South Korea. The performance indicators showed satisfactory results in modeling COVID-19 cases using the Non-linear Autoregressive Exogenous Model (NARX) as the modeling method, and Stringency Index (SI) and Niño Sea Surface Temperature (SST) as model variables. In this study, we showed that the accuracy of SARS-CoV-2 transmission forecasts may be further improved by incorporating both the Niño SST and SI variables and combining these variables with NARX may outperform other models. Future forecasting work by modelers should consider including climate or environmental variables (i.e., Niño SST) to enhance the prediction of transmission and spread of severe acute respiratory syndrome coronavirus 2 (SARS-CoV-2).

Climate Anomalies and Spillover of Bat-Borne Viral Diseases in the Asia-Pacific Region and the Arabian Peninsula

Climate variability and anomalies are known drivers of the emergence and outbreaks of infectious diseases. In this study, we investigated the potential association between climate factors and anomalies, including El Niño Southern Oscillation (ENSO) and land surface temperature anomalies, as well as the emergence and spillover events of bat-borne viral diseases in humans and livestock in the Asia-Pacific region and the Arabian Peninsula. Our findings from time series analyses, logistic regression models, and structural equation modelling revealed that the spillover patterns of the Nipah virus in Bangladesh and the Hendra virus in Australia were differently impacted by climate variability and with different time lags. We also used event coincidence analysis to show that the emergence events of most bat-borne viral diseases in the Asia-Pacific region and the Arabian Peninsula were statistically associated with ENSO climate anomalies. Spillover patterns of the Nipah virus in Bangladesh and the Hendra virus in Australia were also significantly associated with these events, although the pattern and co-influence of other climate factors differed. Our results suggest that climate factors and anomalies may create opportunities for virus spillover from bats to livestock and humans. Ongoing climate change and the future intensification of El Niño events will therefore potentially increase the emergence and spillover of bat-borne viral diseases in the Asia-Pacific region and the Arabian Peninsula.

Long-term environmental surveillance of PM2.5-bound polycyclic aromatic hydrocarbons in Jinan, China (2014-2020): Health risk assessment

We established long-term surveillance sites in Jinan city to monitor PM_2.5 particles (PM2.5) and PM2.5-bound PAHs (2014-2020). The range of PM2.5 was 15-230 µg/m³. The average annual ƩPAH₁₆ were 433 ± 271 ng/m³ (industrial area) and 299 ± 171.8 ng/m³ (downtown). PAHs captured in winter accounted for 61.5% (industrial area) and 59.1% (downtown) of total PAHs. A hazardous seasonal benzo[a]pyrene level was detected in 2015-2016 winter as 14.03 ng/m³ (14 folds of EU standard). The dominant PM2.5-bound PAHs were benzo[b]fluoranthene (24-26%), chrysene (19-20%), benzo[g,h,i]perylene (15%), Indeno(1,2,3-cd)pyrene (12%) and Benzo[a]pyrene (10%). Toxic equivalent quotients of PAHs were 4.93 ng/m³ (industrial area) and 3.13 ng/m³ (downtown). Excess cancer risks (ECRs) were 4.3 × 10^-4 ng/m³ and 2.7 × 10^-4 ng/m³, respectively. The ECRs exceeded EPA regulatory limit of 1 × 10^-6 ng/m³ largely. Non-negligible excess lifetime cancer risks were found as 36 and 26 related cancer incidences per 1,000,000 people. Consistently, local prevalence of lung cancer raise from 56.97/100,000 to 72.38/100,000; the prevalence of thyroid cancer raise from 10.12/100,000 to 45.26/100,000 from 2014 to 2020. Our findings suggest an urgent need to investigate the adverse health effects of PAHs on local population and we call for more strictly restriction on coal consumption and traffic tail gas emission.

Can El Niño-Southern Oscillation Increase Respiratory Infectious Diseases in China? An Empirical Study of 31 Provinces

Respiratory infectious diseases (RID) are the major form of infectious diseases in China, and are highly susceptible to climatic conditions. Current research mainly focuses on the impact of weather on RID, but there is a lack of research on the effect of El Niño–Southern Oscillation (ENSO) on RID. Therefore, this paper uses the system generalized method of moments (SYS-GMM) and the data of 31 provinces in China from 2007 to 2018 to construct a dynamic panel model to empirically test the causality between ENSO and RID morbidity. Moreover, this paper considers the moderating effects of per capita disposable income and average years of education on this causality. The results show that ENSO can positively and significantly impact RID morbidity, which is 5.842% higher during El Niño years than normal years. In addition, per capita disposable income and average years of education can effectively weaken the relationship between ENSO and RID morbidity. Thus, this paper is of great significance for improving the RID early climate warning system in China and effectively controlling the spread of RID.

Alternate patterns of temperature variation bring about very different disease outcomes at different mean temperatures

The dynamics of host-parasite interactions are highly temperature-dependent and may be modified by increasing frequency and intensity of climate-driven heat events. Here, we show that altered patterns of temperature variance lead to an almost order-of-magnitude shift in thermal performance of host and pathogen life-history traits over and above the effects of mean temperature and, moreover, that different temperature regimes affect these traits differently. We found that diurnal fluctuations of ±3°C lowered infection rates and reduced spore burden compared to constant temperatures in our focal host Daphnia magna exposed to the microsporidium parasite Ordospora colligata. In contrast, a 3-day heatwave (+6°C) did not affect infection rates, but increased spore burden (relative to constant temperatures with the same mean) at 16°C, while reducing burden at higher temperatures. We conclude that changing patterns of climate variation, superimposed on shifts in mean temperatures due to global warming, may have profound and unanticipated effects on disease dynamics.

Climate change and zoonoses: A review of the current status, knowledge gaps, and future trends

Emerging infectious diseases (EIDs), especially those with zoonotic potential, are a growing threat to global health, economy, and safety. The influence of global warming and geoclimatic variations on zoonotic disease epidemiology is evident by alterations in the host, vector, and pathogen dynamics and their interactions. The objective of this article is to review the current literature on the observed impacts of climate change on zoonoses and discuss future trends. We evaluated several climate models to assess the projections of various zoonoses driven by the predicted climate variations. Many climate projections revealed potential geographical expansion and the severity of vector-borne, waterborne, foodborne, rodent-borne, and airborne zoonoses. However, there are still some knowledge gaps, and further research needs to be conducted to fully understand the magnitude and consequences of some of these changes. Certainly, by understanding the impact of climate change on zoonosis emergence and distribution, we could better plan for climate mitigation and climate adaptation strategies.

Impacts of El Niño Southern Oscillation on the dengue transmission dynamics in the Metropolitan Region of Recife, Brazil

Background:

This research addresses two questions: (1) how El Niño Southern Oscillation (ENSO) affects climate variability and how it influences dengue transmission in the Metropolitan Region of Recife (MRR), and (2) whether the epidemic in MRR municipalities has any connection and synchronicity.

Methods:

Wavelet analysis and cross-correlation were applied to characterize seasonality, multiyear cycles, and relative delays between the series. This study was developed into two distinct periods. Initially, we performed periodic dengue incidence and intercity epidemic synchronism analyses from 2001 to 2017. We then defined the period from 2001 to 2016 to analyze the periodicity of climatic variables and their coherence with dengue incidence.

Results:

Our results showed systematic cycles of 3-4 years with a recent shortening trend of 2-3 years. Climatic variability, such as positive anomalous temperatures and reduced rainfall due to changes in sea surface temperature (SST), is partially linked to the changing epidemiology of the disease, as this condition provides suitable environments for the Aedes aegypti lifecycle.

Conclusion:

ENSO may have influenced the dengue temporal patterns in the MRR, transiently reducing its main way of multiyear variability (3-4 years) to 2-3 years. Furthermore, when the epidemic coincided with El Niño years, it spread regionally and was highly synchronized.

Impact of El Niño on the dynamics of American cutaneous leishmaniasis in a municipality in the western Amazon

Vector-borne diseases are some of the leading public health problems in the tropics, and their association with climatic anomalies is well known. The current study aimed to evaluate the trend of American cutaneous leishmaniasis cases in the municipality of Manaus, Amazonas-Brazil, and its relationship with climatic extremes (ENSO). The study was carried out using a series of secondary data from notifications on the occurrence of several American cutaneous leishmaniasis cases in the municipality of Manaus between 1990 and 2017 obtained through the Sistema de Informação de Agravos de Notificação. Data regarding temperature, relative humidity, and precipitation for this municipality were derived from the Instituto Nacional de Meteorologia (INMET) and the National Oceanic and Atmospheric Administration (NOAA) websites. Coherence and wavelet phase analysis was conducted to measure the degree of relationship of the occurrence of the cases of cutaneous leishmaniasis and the El Niño-Southern Oscillation (ENSO). The results show that during La Niña events, an increase in American cutaneous leishmaniasis (ACL) cases is anticipated after the increase in rainfall from November, resulting in a more significant number of cases in January, February, and March. It was observed that in the municipality of Manaus, the dynamics of ACL cases are directly influenced by ENSO events that affect environmental variables such as precipitation, temperature, and humidity. Therefore, climatic variations consequently change the ACL incidence dynamics, leading to subsequent increases or decreases in the incidence of ACL cases in the area.

Minireview: Epidemiological impact of arboviral diseases in Latin American countries, arbovirus-vector interactions and control strategies

Mosquitoes are the most crucial insects in public health due to their vector capacity and competence to transmit pathogens, including arboviruses, bacterias and parasites. Re-emerging and emerging arboviral diseases, such as yellow fever virus (YFV), dengue virus (DENV), zika virus (ZIKV), and chikungunya virus (CHIKV), constitute one of the most critical health public concerns in Latin America. These diseases present a significant incidence within the human settlements increasing morbidity and mortality events. Likewise, among the different genus of mosquito vectors of arboviruses, those of the most significant medical importance corresponds to Aedes and Culex. In Latin America, the mosquito vector species of YFV, DENV, ZIKV, and CHIKV are mainly Aedes aegypti and Ae. Albopictus. Ae. aegypti is recognized as the primary vector in urban environments, whereas Ae. albopictus, recently introduced in the Americas, is more prone to rural settings. This minireview focuses on what is known about the epidemiological impact of mosquito-borne diseases in Latin American countries, with particular emphasis on YFV, DENV, ZIKV and CHIKV, vector mosquitoes, geographic distribution, and vector-arbovirus interactions. Besides, it was analyzed how climate change and social factors have influenced the spread of arboviruses and the control strategies developed against mosquitoes in this continent.

Epidemiology of hemorrhagic fever with renal syndrome in Tai'an area

Hemorrhagic fever with renal syndrome (HFRS), a serious threat to human health, is mainly transmitted by rodents in Eurasia. The risk of disease differs according to sex, age, and occupation. Further, temperature and rainfall have some lagging effects on the occurrence of the disease. The quantitative data for these factors in the Tai'an region of China are still unknown. We used a forest map to calculate the risk of HFRS in different populations and used four different mathematical models to explain the relationship between time factors, meteorological factors, and the disease. The results showed that compared with the whole population, the relative risk in rural medical staff and farmers was 5.05 and 2.00, respectively (p < 0.05). Joinpoint models showed that the number of cases decreased by 33.32% per year from 2005 to 2008 (p < 0.05). The generalized additive model showed that air temperature was positively correlated with disease risk from January to June, and that relative humidity was negatively correlated with risk from July to December. From January to June, with an increase in temperature, after 15 lags, the cumulative risk of disease increased at low temperatures. From July to December, the cumulative risk decreased with an increase in the relative humidity. Rural medical staff, farmers, men, and middle-aged individuals were at a high risk of HFRS. Moreover, air temperature and relative humidity are important factors that affect disease occurrence. These associations show lagged and differing effects according to the season.

Divide-and-conquer: machine-learning integrates mammalian and viral traits with network features to predict virus-mammal associations

Our knowledge of viral host ranges remains limited. Completing this picture by identifying unknown hosts of known viruses is an important research aim that can help identify and mitigate zoonotic and animal-disease risks, such as spill-over from animal reservoirs into human populations. To address this knowledge-gap we apply a divide-and-conquer approach which separates viral, mammalian and network features into three unique perspectives, each predicting associations independently to enhance predictive power. Our approach predicts over 20,000 unknown associations between known viruses and susceptible mammalian species, suggesting that current knowledge underestimates the number of associations in wild and semi-domesticated mammals by a factor of 4.3, and the average potential mammalian host-range of viruses by a factor of 3.2. In particular, our results highlight a significant knowledge gap in the wild reservoirs of important zoonotic and domesticated mammals' viruses: specifically, lyssaviruses, bornaviruses and rotaviruses.

Association between socio-environmental factors, coverage by family health teams, and rainfall in the spatial distribution of Zika virus infection in the city of Rio de Janeiro, Brazil, in 2015 and 2016

BACKGROUND

Zika virus (ZIKV) infection caused outbreak in Brazil, in 2015 and 2016. Disorganized urban growth, facilitates the concentration of numerous susceptible and infected individuals. It is useful to understand the mechanisms that can favor the increase in ZIKV incidence, such as areas with wide socioeconomic and environmental diversity. Therefore, the study analyzed the spatial distribution of ZIKV in the city of Rio de Janeiro, Brazil, in 2015 and 2016, and associations between the incidence per 1000 inhabitants and socio-environmental factors.

METHODS

The census tracts were used as the analytical units reported ZIKV cases among the city's inhabitants. Local Empirical Bayesian method was used to control the incidence rates' instability effect. The spatial autocorrelation was verified with Moran's Index and local indicators of spatial association (LISA). Spearman correlation matrix was used to indicate possible collinearity. The Ordinary Least Squares (OLS), Spatial Lag Model (SAR), and Spatial Error Model (CAR) were used to analyze the relationship between ZIKV and socio-environmental factors.

RESULTS

The SAR model exhibited the best parameters: R2 = 0.44, Log-likelihood = - 7482, Akaike Information Criterion (AIC) = 14,980. In this model, mean income between 1 and 2 minimum wages was possible risk factors for Zika occurrence in the localities. Household conditions related to adequate water supply and the existence of public sewage disposal were associated with lower ZIKV cumulative incidence, suggesting possible protective factors against the occurrence of ZIKV in the localities. The presence of the Family Health Strategy in the census tracts was positively associated with the ZIKV cumulative incidence. However, the results show that mean income less than 1 minimum wage were negatively associated with higher ZIKV cumulative incidence.

CONCLUSION

The results demonstrate the importance of socio-environmental variables in the dynamics of ZIKV transmission and the relevance for the development of control strategies.

Gaps in health security related to wildlife and environment affecting pandemic prevention and preparedness, 2007-2020

OBJECTIVE

To describe and quantify the extent of wildlife and environment sector inclusion in country evaluation and prioritization tools for health security, and to provide practical recommendations for global and national action to improve pandemic prevention and preparedness.

METHODS

To assess coverage of wildlife and other environmental aspects, we reviewed major health security reports (including World Organisation for Animal Health Performance of Veterinary Services reports, and World Health Organization Joint External Evaluations and follow-on National Action Plans for Health Security) published by 107 countries and territories. We extracted information on stated coverage gaps, wildlife surveillance systems and priority diseases. We also searched National Biodiversity Strategies and Action Plans published by 125 countries to assess whether disease surveillance or prevention activities were included.

FINDINGS

We noted that the occurrence frequency of keywords indicative of wildlife, environment, biodiversity and climate factors varied with type of report and between countries. We found that more than half (57.9%, 62/107) of the reporting countries did not provide any evidence of a functional wildlife health surveillance programme. Most countries (83.2%, 89/107) indicated specific gaps in operations, coordination, scope or capacity. Only eight of the 125 countries (6.4%) publishing a National Biodiversity Strategy and Action Plan reported tangible activities related to wildlife health or zoonotic disease.

CONCLUSION

Overall, despite their importance for pandemic prevention, wildlife and environmental considerations are neglected in health security priorities and plans. Strengthening wildlife health capacity and operations should be emphasized in One Health efforts to monitor and mitigate known and novel disease risks.

Sea surface temperature variability and ischemic heart disease outcomes among older adults

Ischemic heart disease (IHD) is one of the leading causes of death worldwide. While extreme summer surface air temperatures are thought to be a risk factor for IHD, it is unclear whether large-scale climate patterns also influence this risk. This multi-national population-based study investigated the association between summer Pacific and Atlantic sea surface temperature (SST) variability and annual acute myocardial infarction (AMI) or IHD event rates among older adults residing in North America and the United Kingdom. Overall, a shift from cool to warm phase of the El Niño Southern Oscillation (ENSO) was associated with reduced AMI admissions in western Canada (adjusted rate ratio [RR] 0.89; 95% CI, 0.80-0.99), where this climate pattern predominatly forces below-normal cloud cover and precipitation during summertime, and increased AMI deaths in western United States (RR 1.09; 95% CI, 1.04-1.15), where it forces increased cloud cover and precipitation. Whereas, the Atlantic Multidecadal Oscillation (AMO) during a strong positive phase was associated with reduced AMI admissions in eastern Canada (RR 0.93; 95% CI, 0.87-0.98) and increased IHD mortality during summer months in the United Kingdom (RR 1.08; 95% CI, 1.03-1.14). These findings suggest that SST variability can be used to predict changes in cardiovascular event rates in regions that are susceptible.

Leaving no stone unturned in light of the COVID-19 faecal-oral hypothesis? A water, sanitation and hygiene (WASH) perspective targeting low-income countries

The human coronavirus disease (COVID-19) is now a global pandemic. Social distancing, hand hygiene and the use of personal protective equipment dominate the current fight against COVID-19. In developing countries, the need for clean water provision, sanitation and hygiene has only received limited attention. The current perspective examines the latest evidence on the occurrence, persistence and faecal-oral transmission of severe acute respiratory syndrome coronavirus-2 (SARS-CoV-2), the etiological agent causing COVID-19. Evidence shows that SARS-CoV-2 proliferate in the human gastrointestinal system, and is shed via faeces. SARS-CoV-2 can survive and remain viable for up to 6 to 9 days on surfaces. Recent wastewater-based epidemiological studies from several countries also detected SARS-CoV-2 RNA in raw wastewaters. Shell disorder analysis shows that SARS-CoV-2 has a rigid outer shell conferring resilience, and a low shell disorder conferring moderate potential for faecal-oral transmission. Taken together, these findings point to potential faecal-oral transmission of SARS-CoV-2, which may partly explain its rapid transmission. Three potential mechanisms may account for SARS-CoV-2 faecal-oral transmission: (1) untreated contaminated drinking water, (2) raw and poorly cooked marine and aquatic foods from contaminated sources, (3) raw wastewater-based vegetatble production systems (e.g., salads) and aquaculture, and (4) vector-mediated transmission from faecal sources to foods, particularly those from open markets and street vending. SARS-CoV-2 faecal-oral transmission could be particularly high in developing countries due to several risk factors, including; (1) poor drinking water, wastewater and sanitation infrastructure, (2) poor hygiene and food handling practices, (3) unhygienic and rudimentary funeral practices, including home burials close to drinking water sources, and (4) poor social security and health care systems with low capacity to cope with disease outbreaks. Hence, clean drinking water provision, proper sanitation, food safety and hygiene could be critical in the current fight against COVID-19. Future research directions on COVID-19 faecal-oral transmission are highlighted.

COVID-19 and Ecosyndemic Vulnerability: Implications for El Niño-Sensitive Countries in Latin America

Latin America has emerged as an epicenter of the COVID-19 pandemic. Brazil, Peru, and Ecuador report some of the highest COVID-19 rates of incidence and deaths in the region. These countries also face synergistic threats from multiple infectious diseases (that is, ecosyndemic) and quasi-periodic El Niño-related hazards every few years. For example, Peru, which is highly sensitive to El Niño, already copes with an ecosyndemic health burden that heightens during and following weather and climate extreme events. Using an ecosyndemic lens, which draws on a multi-disease hazard context of place, this commentary highlights the importance of El Niño as a major factor that not only may aggravate COVID-19 incidence in the future, but also the broader health problem of ecosyndemic vulnerability in Latin America.

Diverging functional strategies but high sensitivity to an extreme drought in tropical dry forests

Extreme drought events have negative effects on forest diversity and functioning. At the species level, however, these effects are still unclear, as species vary in their response to drought through specific functional trait combinations. We used long-term demographic records of 21,821 trees and extensive databases of traits to understand the responses of 338 tropical dry forests tree species to ENSO₂₀₁₅ , the driest event in decades in Northern South America. Functional differences between species were related to the hydraulic safety-efficiency trade-off, but unexpectedly, dominant species were characterised by high investment in leaf and wood tissues regardless of their leaf phenological habit. Despite broad functional trait combinations, tree mortality was more widespread in the functional space than tree growth, where less adapted species showed more negative net biomass balances. Our results suggest that if dry conditions increase in this ecosystem, ecological functionality and biomass gain would be reduced.

Transdisciplinary Research Priorities for Human and Planetary Health in the Context of the 2030 Agenda for Sustainable Development

Human health and wellbeing and the health of the biosphere are inextricably linked. The state of Earth's life-support systems, including freshwater, oceans, land, biodiversity, atmosphere, and climate, affect human health. At the same time, human activities are adversely affecting natural systems. This review paper is the outcome of an interdisciplinary workshop under the auspices of the Future Earth Health Knowledge Action Network (Health KAN). It outlines a research agenda to address cross-cutting knowledge gaps to further understanding and management of the health risks of these global environmental changes through an expert consultation and review process. The research agenda has four main themes: (1) risk identification and management (including related to water, hygiene, sanitation, and waste management); food production and consumption; oceans; and extreme weather events and climate change. (2) Strengthening climate-resilient health systems; (3) Monitoring, surveillance, and evaluation; and (4) risk communication. Research approaches need to be transdisciplinary, multi-scalar, inclusive, equitable, and broadly communicated. Promoting resilient and sustainable development are critical for achieving human and planetary health.

Perception and knowledge of the effect of climate change on infectious diseases within the general public: A multinational cross-sectional survey-based study

Infectious diseases are emerging and re-emerging due to climate change. Understanding how climate variability affects the transmission of infectious diseases is important for both researchers and the general public. Yet, the widespread knowledge of the general public on this matter is unknown, and quantitative research is still lacking. A survey was designed to assess the knowledge and perception of 1) infectious diseases, 2) climate change and 3) the effect of climate change on infectious diseases. Participants were recruited via convenience sampling, and an anonymous cross-sectional survey with informed consent was distributed to each participant. Descriptive and inferential analyses were performed primarily focusing on the occupational background as well as nationality of participants. A total of 458 individuals participated in this study, and most participants were originally from Myanmar, the Netherlands, Spain, United Kingdom and the United States. Almost half (44%) had a background in natural sciences and had a higher level of knowledge on infectious diseases compared to participants with non-science background (mean score of 12.5 and 11.2 out of 20, respectively). The knowledge of the effect of climate change on infectious diseases was also significantly different between participants with and without a background in natural sciences (13.1 and 11.8 out of 20, respectively). The level of knowledge on various topics was highly correlated with nationality but not associated with age. The general population demonstrated a high awareness and strong knowledge of climate change regardless of their background in natural sciences. This study exposes a knowledge gap in the general public regarding the effect of climate change on infectious diseases, and highlights that different levels of knowledge are observed in groups with differing occupations and nationalities. These results may help to develop awareness interventions for the general public.

Farm-Level Risk Factors of Increased Abortion and Mortality in Domestic Ruminants during the 2010 Rift Valley Fever Outbreak in Central South Africa

(1) Background: Rift Valley fever (RVF) outbreaks in domestic ruminants have severe socio-economic impacts. Climate-based continental predictions providing early warnings to regions at risk for RVF outbreaks are not of a high enough resolution for ruminant owners to assess their individual risk. (2) Methods: We analyzed risk factors for RVF occurrence and severity at the farm level using the number of domestic ruminant deaths and abortions reported by farmers in central South Africa during the 2010 RVF outbreaks using a Bayesian multinomial hurdle framework. (3) Results: We found strong support that the proportion of days with precipitation, the number of water sources, and the proportion of goats in the herd were positively associated with increased severity of RVF (the numbers of deaths and abortions). We did not find an association between any risk factors and whether RVF was reported on farms. (4) Conclusions: At the farm level we identified risk factors of RVF severity; however, there was little support for risk factors of RVF occurrence. The identification of farm-level risk factors for Rift Valley fever virus (RVFV) occurrence would support and potentially improve current prediction methods and would provide animal owners with critical information needed in order to assess their herd's risk of RVFV infection.

Geomatics and EO Data to Support Wildlife Diseases Assessment at Landscape Level: A Pilot Experience to Map Infectious Keratoconjunctivitis in Chamois and Phenological Trends in Aosta Valley (NW Italy)

Geomatics and satellite remote sensing offer useful analysis tools for several technical-scientific fields. This work, with reference to a regional case of study, investigates remote sensing potentialities for describing relationships between environment and diseases affecting wildlife at landscape level in the light of climate change effects onto vegetation. Specifically, the infectious keratoconjunctivitis (IKC) of chamois (Rupicapra rupicapra L.) in Aosta Valley (NW Italy) was investigated at the regional level. IKC (Mycoplasma conjunctivae) is a contagious disease for domestic and wild ruminants (Caprinae and Ovinae). Two types of analysis were performed: one aimed at exploring by remotely sensed data phenological metrics (PMs) and evapotranspiration (ET) trends of vegetation in the area; one investigating the correlation between PMs and ET, versus IKC prevalence. The analysis was based on TERRA MODIS image time series ranging from 2000 to 2019. Ground data about IKC were available for a shorter time range: 2009–2019. Consequently, PMs and ET trend investigations were focused on the whole times range (2000–2019); conversely, correlation analysis was achieved with reference to the reduced 2009–2019 period. The whole study was based on freely available data from public archives. MODIS products, namely MOD13Q1 v.6 and MOD16A2, were used to derive PM and ET trends, respectively. Shuttle Radar Topography Mission (SRTM) Digital Terrain Model (DTM) was used to describe local topography; CORINE Land Cover map was adopted to describe land use classes. PMs and ET (as derivable from EO data) proved to significantly changed their values in the last 20 years, with a continuous progressive trend. As far as correlation analysis was concerned, ET and some PMs (specifically, End of Season (EOS) and Length of Season (LOS) proved significantly condition IKC prevalence. According to results, the proposed methodology can be retained as an effective tool for supporting public health and eco-pathological sectors. Specifically, it can be intended for a continuous monitoring of effects that climatic dynamics determine onto wild animals in the Alpine area, included diseases and zoonosis, moving future environmental management and planning towards the One Health perspective.